@@ -253,6 +253,7 @@ def init_single_subject_wf(subject_id):
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spaces = spaces ,
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t1w = subject_data ["t1w" ],
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)
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+ anat_preproc_wf .__desc__ = f"\n \n { anat_preproc_wf .__desc__ } "
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# fmt:off
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workflow .connect ([
@@ -290,17 +291,16 @@ def init_single_subject_wf(subject_id):
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# Append the dMRI section to the existing anatomical excerpt
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# That way we do not need to stream down the number of DWI datasets
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- anat_preproc_wf .__postdesc__ = (
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- ( anat_preproc_wf .__postdesc__ or "" )
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- + f"""
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+ anat_preproc_wf .__postdesc__ = f""" \
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+ { anat_preproc_wf .__postdesc__ or '' }
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+
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Diffusion data preprocessing
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: For each of the { len (subject_data ["dwi" ])} DWI scans found per subject
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(across all sessions), the gradient table was vetted and converted into the *RASb*
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format (i.e., given in RAS+ scanner coordinates, normalized b-vectors and scaled b-values),
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and a *b=0* average for reference to the subsequent steps of preprocessing was calculated.
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"""
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- )
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# SDC Step 0: Determine whether fieldmaps can/should be estimated
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fmap_estimators = None
@@ -360,6 +360,12 @@ def init_single_subject_wf(subject_id):
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output_dir = str (output_dir ),
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subject = subject_id ,
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)
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+ fmap_wf .__desc__ = f"""
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+ *B<sub>0</sub>* fieldmap data preprocessing
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+
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+ : A total of { len (fmap_estimators )} fieldmaps were found available within the input
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+ BIDS structure for this particular subject.
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+ """
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# TODO: Requires nipreps/sdcflows#147
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for dwi_preproc_wf in dwi_preproc_list :
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